Marcelo Grave

Orcid: 0000-0003-1738-332X

According to our database1, Marcelo Grave authored at least 12 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Small Models Exhibit Limited Answer Consistency in Repetition Trials of the Multiple-Choice MMLU-Redux and MedQA Benchmarks.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
CAT: A Metric-Driven Framework for Analyzing the Consistency-Accuracy Relation of LLMs under Controlled Input Variations.
CoRR, December, 2025

Exploring Human Perceptions of AI Responses: Insights from a Mixed-Methods Study on Risk Mitigation in Generative Models.
CoRR, December, 2025

Improving Score Reliability of Multiple Choice Benchmarks with Consistency Evaluation and Altered Answer Choices.
CoRR, November, 2025

A methodological analysis of prompt perturbations and their effect on attack success rates.
CoRR, November, 2025

The Non-Determinism of Small LLMs: Evidence of Low Answer Consistency in Repetition Trials of Standard Multiple-Choice Benchmarks.
CoRR, September, 2025

A Comprehensive Evaluation framework of Alignment Techniques for LLMs.
CoRR, August, 2025

2024
Creating an African American-Sounding TTS: Guidelines, Technical Challenges, and Surprising Evaluations.
Proceedings of the 29th International Conference on Intelligent User Interfaces, 2024

2023
"This means nothing to me": Building credibility in conversational systems.
Proceedings of the 5th International Conference on Conversational User Interfaces, 2023

2022
How can AI leverage alternative criteria and suggest a better way to measure credit worthiness and economic growth?
Proceedings of the CUI 2022: 4th Conference on Conversational User Interfaces, Glasgow, United Kingdom, July 26, 2022

2020
Creating Corpora for Seq2Seq Tone Rephrasing Using Social Media Posts.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

From Disjoint Sets to Parallel Data to Train Seq2Seq Models for Sentiment Transfer.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020


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